开放政府数据混搭的法律本体

Martynas Mockus, M. Palmirani
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引用次数: 18

摘要

关联开放政府数据的一个重要支柱是能够通过使用共同的本体来混合数据集,从而推断出新的知识。开发者要整合的开放政府数据集可能要遵守不同的许可、法律声明、使用条款以及来自多个司法管辖区的适用法律和法规。在这个复杂的生态系统中,需要创建由本体支持的半自动工具,以帮助公共部门信息的技术重用者根据其预期目的并遵守管理数据重用权的法律义务来利用数据集。不幸的是,一些研究人员可能会避免考虑所有适用于开放政府数据领域的法律框架,并将他们的调查限制在许可证领域。为了更广泛、合规地利用混合开放数据,我们分析了欧盟(EU)公共部门信息(PSI)再利用的法律框架、欧盟数据库指令和版权框架以及其他适用于开放政府数据集的法律来源(例如许可证、法律声明、使用条款)。从这一深入分析中,我们现在对用于混搭模型的开放政府数据许可框架本体(OGDL4M)中的几个主要概念进行建模。早前就有创作共用或开放许可的本体,但它们没有预料到开放政府法规所产生的其他法律约束。OGDL4M本体将用于限定数据集,以提高其法律注释的准确性。本体论还旨在将每个适用的法律规则与官方法律文本联系起来,以便指导法律专家和再使用者找到原始来源。本文旨在深入介绍OGDL4M本体的模块,并描述一些初步评价。
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Legal Ontology for Open Government Data Mashups
An important pillar of Linked Open Government Data is to be able to mix datasets by using common ontologies in order to infer new knowledge. The open government datasets to be mashed-up by developers may be subject to distinct licenses, legal notices, terms of use, and applicable law and regulations from multiple jurisdictions. Within this complex ecosystem there is a need to create semi-automatic tools supported by an ontology to help technical reusers of Public Sector Information to utilize datasets according to their intended purpose and in compliance with the legal obligations that govern the rights to reuse the data. Unfortunately, some researchers may avoid considering all the legal frameworks that apply in the domain of Open Government Data and limit their investigation to only the area of licenses. To enable wider, compliant utilisation of mashed-up open data, we have analysed the European Union (EU) legal framework of reuse of Public Sector Information (PSI), the EU Database Directive and copyright framework and other legal sources (e.g., licenses, legal notices, terms of use) that can apply to open government Datasets. From this deep analysis we now model several major concepts in an Ontology of Open Government Data Licenses Framework for a Mash-up Model (OGDL4M). There have been earlier ontologies for creative commons or open licenses, but they did not anticipate the other legal constraints that arise from Open Government regulations. The OGDL4M ontology will be used for qualifying datasets in order to improve the accuracy of their legal annotation. The Ontology also aims to connect each applicable legal rule to official legal texts in order to direct legal experts and reusers to primary sources. This paper aims to present the modules of the OGDL4M ontology in depth and to describe some preliminary evaluation.
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